21 references to NumberOfNodes
Microsoft.ML.FastTree (13)
RegressionTree.cs (5)
108
if (nodeIndex < 0 || nodeIndex >=
NumberOfNodes
)
109
throw Contracts.Except($"The input index, {nodeIndex}, is invalid. Its valid range is from 0 (inclusive) to {
NumberOfNodes
} (exclusive).");
125
if (nodeIndex < 0 || nodeIndex >=
NumberOfNodes
)
126
throw Contracts.Except($"The input node index, {nodeIndex}, is invalid. Its valid range is from 0 (inclusive) to {
NumberOfNodes
} (exclusive).");
146
/// node0->leaf3, node1->leaf1, node1->leaf2, <see cref="
NumberOfNodes
"/> and <see cref="NumberOfLeaves"/> should
Utils\RegressionTreeBaseUtils.cs (8)
26
var numberOfRows = trees.Select(tree => tree.
NumberOfNodes
).Sum() + trees.Select(tree => tree.NumberOfLeaves).Sum();
44
treeWeightsList.AddRange(Enumerable.Repeat(treeWeights[i], trees[i].
NumberOfNodes
+ trees[i].NumberOfLeaves));
47
treeId.AddRange(Enumerable.Repeat(i, trees[i].
NumberOfNodes
+ trees[i].NumberOfLeaves));
50
isLeaf.AddRange(Enumerable.Repeat(new ReadOnlyMemory<char>("Tree node".ToCharArray()), trees[i].
NumberOfNodes
));
74
leafValues.AddRange(Enumerable.Repeat(0d, trees[i].
NumberOfNodes
));
81
for (int j = 0; j < trees[i].
NumberOfNodes
; j++)
124
leafSamples.AddRange(Enumerable.Repeat(new VBuffer<double>(), quantileTrees[i].
NumberOfNodes
));
125
leafSampleWeights.AddRange(Enumerable.Repeat(new VBuffer<double>(), quantileTrees[i].
NumberOfNodes
));
Microsoft.ML.IntegrationTests (7)
IntrospectiveTraining.cs (7)
58
Assert.Equal(4, tree.
NumberOfNodes
);
59
Assert.Equal(tree.SplitGains.Count, tree.
NumberOfNodes
);
60
Assert.Equal(tree.NumericalSplitThresholds.Count, tree.
NumberOfNodes
);
102
Assert.Equal(4, tree.
NumberOfNodes
);
103
Assert.Equal(tree.SplitGains.Count, tree.
NumberOfNodes
);
104
Assert.Equal(tree.NumericalSplitThresholds.Count, tree.
NumberOfNodes
);
120
for (int i = 0; i < finalTree.
NumberOfNodes
; ++i)
Microsoft.ML.Tests (1)
TrainerEstimators\TreeEstimators.cs (1)
883
for (int j = 0; j < trees[i].
NumberOfNodes
; j++)